POS0558 A INFLAMMATORY FACTOR-BASED NOMOGRAM PREDICTS FIRST REMISSION TIME OF RHEUMATOID ARTHRITIS PATIENTS WITH BASELINE GALECTIN-9
Authors: Z. Sun, X. Liu, F. Wang, J. Sun, Y. Sui, Q. Che, Q. Shu
Journal: Annals of the Rheumatic Diseases (2022)

<h3>Background</h3> Rheumatoid arthritis (RA) is an autoimmune disease. The core treatment principle of RA is to achieve remission or low disease activity as soon as possible to ensure optimal outcomes. Predicting the first remission time according to the patient's risk factors is very important for the choice of treatment scheme. <h3>Objectives</h3> We aimed to verify the prognostic value of inflammatory factors in RA and establish a nomogram based on Human Interleukin-6(IL-6), Galectin-9(Gal-9)and disease activity to predict the first remission time after conventional synthetic DMARDstreatment. <h3>Methods</h3> 184 RA active patients(DAS28-ESR&gt; 3.2, ACR 1987 criteria or EULAR 2010 criteria) were enrolled in the rheumatology department of Qilu Hospital of Shandong University from June 2014 to June 2020.129 patients were assigned to the development cohort and 55 patients were assigned to the validation cohort randomly. Baseline clinical data and plasma were collected. The expressions of Tumour Necrosis Factor α (TNF-α), Vascular Endothelial Growth Factor (VEGF), IL-6 and Gal-9 in plasma of RA patients were detected by ELISA. All patients were treated with csDMARDs and we recorded activity of each follow-up visit until 36 months. Lasso regression and Cox regression analysis were used to screen the 14 variables (including activity indices and cytokines) at baseline, and the prediction model was established to draw the nomogram. <h3>Results</h3> Patient age, CRP, IL-6, Gal-9, HAQ and DAS28-ESR were the significant prognostic factors in the lasso and Cox regression analyses, especially Gal-9. The multivariate analysis revealed that IL-6≤ 9.04 pg/ml(<i>HR</i> =0.54, 95% <i>CI</i>:0.31–0.95), Gal-9≤ 4490 pg/ml(<i>HR</i> =0.43, 95% <i>CI</i>:0.21–0.89) were independent protective factors (Table 1). Above-mentioned six factors were included in our model as predictors (Figure 1). The resulting model containing six factors had good discrimination ability in both the development cohort (C-index, 0.729) and the validation cohort (C-index, 0.710). Time-dependent ROC curve (Figure 2), calibration analysis (Figure 3) and decision curve analysis (DCA) show that the nomogram has significant discriminant power, stability and clinical practicability in predicting the first remission time. <h3>Conclusion</h3> We constructed and validated a nomogram with baseline activity indices and cytokines that can predict first remission time in RA patients after csDMARDs treatment. Using this simple-to-use model with plasma Gal-9 at baseline, the remission rate can be determined for an individual patient and could be useful for the early identification of high-risk patients. <h3>References</h3> [1]SUN J, SUI Y, WANG Y, et al. Galectin-9 expression correlates with therapeutic effect in rheumatoid arthritis [J]. Scientific reports, 2021, 11(1): 5562. [2]ZHANG L, CHEN F, GENG S, et al. Methotrexate (MTX) Plus Hydroxychloroquine versus MTX Plus Leflunomide in Patients with MTX-Resistant Active Rheumatoid Arthritis: A 2-Year Cohort Study in Real World [J]. Journal of inflammation research, 2020, 13: 1141-50. [3]FORNARO M, CACCIAPAGLIA F, LOPALCO G, et al. Predictors of long-term clinical remission in rheumatoid arthritis [J]. European journal of clinical investigation, 2021, 51(2): e13363. <h3>Acknowledgements</h3> Funded by ECCM Program of Clinical Research Center of Shandong University (No. 2021SDUCRCB010) <h3>Disclosure of Interests</h3> None declared.